Summary of Eureka: Evaluating and Understanding Large Foundation Models, by Vidhisha Balachandran et al.
Eureka: Evaluating and Understanding Large Foundation Models
by Vidhisha Balachandran, Jingya Chen, Neel Joshi, Besmira Nushi, Hamid Palangi, Eduardo Salinas, Vibhav Vineet, James Woffinden-Luey, Safoora Yousefi
First submitted to arxiv on: 13 Sep 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Rigorous evaluation is crucial in Artificial Intelligence to assess the state of the art and guide scientific advances. However, evaluating AI models is challenging due to factors like benchmark saturation, lack of transparency, and difficulties in measuring generative tasks’ performance. To address these challenges, we introduce three contributions: Eureka, an open-source framework for standardized evaluations; Eureka-Bench, a collection of benchmarks testing fundamental language and multimodal capabilities; and an analysis of 12 state-of-the-art models using Eureka. Our findings show that different models excel in various areas, but there is no single “best” model. Instead, each has its strengths and weaknesses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial Intelligence evaluation is important to understand how well AI models work. The problem is that it’s hard to compare them fairly because of issues like too many benchmarks, unclear methods, and difficulty measuring some tasks. We’re solving this by creating three things: Eureka, a framework for fair evaluations; Eureka-Bench, a set of tests for language and visual skills; and an analysis of 12 top AI models. Our results show that each model is good at something different, but none are the best overall. |
